Signal Grass (Brachiaria decumbens) Toxicity in Grazing Ruminants

Signal grass (Brachiaria decumbens) is a highly productive tropical grass that is widespread through South America, Australia, Indonesia, Vanuatu and Malaysia due to its adaptation to a wide range of soil types and environments. Animal production from these B. decumbens pastures is highly variable due to sporadic outbreaks of photosensitisation associated with low growth rates of young animals, anorexia and wasting. The identification of B. decumbens toxicity through clinical signs may grossly underestimate the impact and severity of the disease. Affected animals without clinical signs have elevated serum liver enzyme concentrations resulting from blockage of the bile ducts by birefringent crystals, identified as calcium salts of steroidal saponins found in leaves and stems. The concentrations of the steroidal saponins vary through the year and within the plant. Young, green leaves contain 5–10 times the saponin concentration of mature leaves indicating that B. decumbens pastures are likely to be more toxic during sprouting and early growth. Previous exposure, selective grazing, and avoiding toxic leaves may partly explain apparent resistance of some animals to B. decumbens toxicity. Further research is needed to define growing conditions that produce elevated saponin levels and to investigate the impact of B. decumbens on rumen function

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Selection of patients for large mailed fecal immunochemical test colorectal cancer screening outreach programs: A systematic review.

ObjectiveDigital health care offers an opportunity to scale and personalize cancer screening programs, such as mailed outreach for colorectal cancer (CRC) screening. However, studies that describe the patient selection strategy and process for CRC screening are limited. Our objective was to evaluate implementation strategies for selecting patients for CRC screening programs in large health care systems.MethodsWe conducted a systematic review of 30 studies along with key informant surveys and interviews to describe programmatic implementation strategies for selecting patients for CRC screening. PubMed and Embase were searched since inception through December 2018, and hand searches were performed of the retrieved reference lists but none were incorporated (n = 0). No language exclusions were applied.ResultsCommon criteria for outreach exclusion included: being up-to-date with routine CRC screening (n = 22), comorbidities (n = 20), and personal history (n = 22) or family history of cancer (n = 9). Key informant surveys and interviews were performed (n = 28) to understand data sources and practices for patient outreach selection, and found that 13 studies leveraged electronic medical care records, 10 studies leveraged a population registry (national, municipal, community, health), 4 studies required patient opt-in, and 1 study required primary care provider referral. Broad ranges in fecal immunochemical test completion were observed in community clinic (n = 8, 31.0-59.6%), integrated health system (n = 5, 21.2-82.7%), and national regional CRC screening programs (n = 17, 23.0-64.7%). Six studies used technical codes, and four studies required patient self-reporting from a questionnaire to participate.ConclusionThis systematic review provides health systems with the diverse outreach practices and technical tools to support efforts to automate patient selection for CRC screening outreach

Selection of patients for large mailed fecal immunochemical test colorectal cancer screening outreach programs: A systematic review.

ObjectiveDigital health care offers an opportunity to scale and personalize cancer screening programs, such as mailed outreach for colorectal cancer (CRC) screening. However, studies that describe the patient selection strategy and process for CRC screening are limited. Our objective was to evaluate implementation strategies for selecting patients for CRC screening programs in large health care systems.MethodsWe conducted a systematic review of 30 studies along with key informant surveys and interviews to describe programmatic implementation strategies for selecting patients for CRC screening. PubMed and Embase were searched since inception through December 2018, and hand searches were performed of the retrieved reference lists but none were incorporated (n = 0). No language exclusions were applied.ResultsCommon criteria for outreach exclusion included: being up-to-date with routine CRC screening (n = 22), comorbidities (n = 20), and personal history (n = 22) or family history of cancer (n = 9). Key informant surveys and interviews were performed (n = 28) to understand data sources and practices for patient outreach selection, and found that 13 studies leveraged electronic medical care records, 10 studies leveraged a population registry (national, municipal, community, health), 4 studies required patient opt-in, and 1 study required primary care provider referral. Broad ranges in fecal immunochemical test completion were observed in community clinic (n = 8, 31.0-59.6%), integrated health system (n = 5, 21.2-82.7%), and national regional CRC screening programs (n = 17, 23.0-64.7%). Six studies used technical codes, and four studies required patient self-reporting from a questionnaire to participate.ConclusionThis systematic review provides health systems with the diverse outreach practices and technical tools to support efforts to automate patient selection for CRC screening outreach